high performance computing on graphics processing units: hgpu.org

The precise semantics of floating-point arithmetic programs depends on the execution platform, including the compiler and the target hardware. Platform dependencies are particularly pronounced for arithmetic-intensive parallel numeric programs and infringe on the highly desirable goal of software portability (which is nonetheless promised by heterogeneous computing frameworks like OpenCL): the same program run on the […]

Modern applications including graphics, multimedia, web search, and data analytics not only can benefit from acceleration, but also exhibit significant degrees of tolerance to imprecise computation. This amenability to approximation provides an opportunity to trade quality of the results for higher performance and better resource utilization. Exploiting this opportunity is particularly important for FPGA accelerators […]

The effective deployment of applications exhibiting irregular nested parallelism on GPUs is still an open problem. A naive mapping of irregular code onto the GPU hardware often leads to resource underutilization and, thereby, limited performance. In this work, we focus on two computational patterns exhibiting nested parallelism: irregular nested loops and parallel recursive computations. In […]

We present a parallel algorithm for finding the shortest path whose total weight is smaller than a pre-determined value. The passage times over the edges are assumed to be positive integers. In each step the processing elements are not analyzing the entire graph. Instead they are focusing on a subset of vertices called active vertices. […]

The generic matrix-matrix multiplication (GEMM) is arguably the most popular computational kernel of the 20th century. Yet, surprisingly, no common methodology for evaluating GEMM performance has been established over the many decades of using GEMM for comparing architectures, compilers and ninja-class programmers. We introduce GEMMbench, a framework and methodology for evaluating performance of GEMM implementations. […]

Climbing Mont Blanc (CMB) is an open online judge used for training in energy efficient programming of state-of-the-art heterogeneous multicores. It uses an Odroid-XU3 board from Hardkernel with an Exynos Octa processor and integrated power sensors. This processor is three-way heterogeneous containing 14 different cores of three different types. The board currently accepts C and […]

We consider the problem of conducting large experimental campaigns in computer science research. Most research efforts require a certain level of bookkeeping of results. This is manageable via quick, on-the-fly infrastructure implementations. However, it becomes a problem for large-scale testing initiatives, especially as the needs of the project evolve along the way. We look at […]

Secure hash algorithms (SHAs) are important components of cryptographic applications. SHA performance on central processing units (CPUs) is slow, therefore, acceleration must be done using hardware such as Field Programmable Gate Arrays (FPGAs). Considerable work has been done in academia using FPGAs to accelerate SHAs. These designs were implemented using Hardware Description Language (HDL) based […]

Heterogeneous systems, more specifically CPU – GPGPU platforms, have gained a lot of attention due to the excellent speedups GPUs can achieve with such little amount of energy consumption. Anyhow, not everything is such a good story, the complex programming models to get the maximum exploitation of the devices and data movement overheads are some […]

State-of-the-art mobile system-on-chips (SoC) include heterogeneity in various forms for accelerated and energy-efficient execution of diverse range of applications. The modern SoCs now include programmable cores such as CPU and GPU with very different functionality. The SoCs also integrate performance heterogeneous cores with different power-performance characteristics but the same instruction-set architecture such as ARM big.LITTLE. […]

1st SYCL workshop (SYCL’16) – co-located with PPoPP’16 Barcelona, Spain Sunday, 13th March, 2016 http://conf.researchr.org/track/PPoPP-2016/SYCL-2016-papers SYCL (sɪkəl – as in sickle) is a royalty-free, cross-platform C++ abstraction layer that builds on the underlying concepts, portability and efficiency of OpenCL, while adding the ease-of-use and flexibility of C++. For example, SYCL enables single source development where […]

GPUs can enable significant performance improvements for certain classes of data parallel applications and are widely used in recent computer systems. However, GPU execution currently requires explicit low-level operations such as 1) managing memory allocations and transfers between the host system and the GPU, 2) writing GPU kernels in a low-level programming model such as […]